Plot a scatter plot of a binary variable with smoothing curve.

Plot the scatter plot of a binary variable with a smoothing curve.

BinaryYScatterPlot(
  frame,
  xvar,
  yvar,
  title,
  ...,
  se = FALSE,
  use_glm = TRUE,
  point_color = "black",
  smooth_color = "blue"
)

Arguments

frame	data frame to get values from
xvar	name of the independent column in frame
yvar	name of the dependent (output or result to be modeled) column in frame
title	title to place on plot
...	no unnamed argument, added to force named binding of later arguments.
se	if TRUE, add error bars (defaults to FALSE). Ignored if useGLM is TRUE
use_glm	if TRUE, "smooths" with a one-variable logistic regression (defaults to TRUE)
point_color	color for points
smooth_color	color for smoothing line

Details

The points are jittered for legibility. By default, a logistic regression fit is used, so that the smoothing curve represents the probability of y == 1 (as fit by the logistic regression). If use_glm is set to FALSE, a standard smoothing curve (either loess or a spline fit) is used.

Examples

set.seed(34903490)
x = rnorm(50)
y = 0.5*x^2 + 2*x + rnorm(length(x))
frm = data.frame(x=x,y=y,yC=y>=as.numeric(quantile(y,probs=0.8)))
frm$absY <- abs(frm$y)
frm$posY = frm$y > 0
frm$costX = 1
WVPlots::BinaryYScatterPlot(frm, "x", "posY",
   title="Example 'Probability of Y' Plot")